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22-Project Report on Rainfall-Runoff Modelling of Sutlej River Basin India Using Soft Computing Techniques.

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dc.contributor.author Singh, Jatin Kumar
dc.contributor.author Under the Guidance of Kumar, A. R. Senthil
dc.date.accessioned 2025-08-11T10:04:00Z
dc.date.available 2025-08-11T10:04:00Z
dc.date.issued 2016
dc.identifier.uri http://117.252.14.250:8080/jspui/handle/123456789/7702
dc.description.abstract Artificial Neural Network (ANN) is a very useful data modeling tool that is able to capture and represent complex input and output relationships. The advantage of ANN lies in its ability to represent both linear and non-linear relationships and in its ability to learn these relationships directly from the data being modeled. Modeling of rainfall runoff relationship is important in view of the many uses of water resources such as hydropower generation, irrigation, water supply and flood control. This study is to purposefully develop a rainfall runoff model for rainfall-runoff modeling in Sutlej river basin, India using soft computing techniques such as Artificial Neural Network (ANN), Radial Basis Function (RBF) and Fuzzy Logic. Training and simulation was done using Matlab 6.5.1 software with varying parameters to obtain the optimum result. en_US
dc.language.iso en en_US
dc.publisher National Institute of Hydrology en_US
dc.subject Rainfall-Runoff Modelling en_US
dc.subject Sutlej River en_US
dc.subject Soft Computing Techniques en_US
dc.subject India en_US
dc.subject Artificial Neural Network en_US
dc.subject ANN en_US
dc.title 22-Project Report on Rainfall-Runoff Modelling of Sutlej River Basin India Using Soft Computing Techniques. en_US
dc.type Technical Report en_US


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